Control strategies of greenhouse climate for vegetables production

Abstract

The most extended control in the greenhouse industry across the world is the classical Proportional-Integral-Derivative control (PID) (Ogata 2002; Kamp and Timmerman 1996; Bakker et al. 1995; Hanan 1998). The greenhouse environment is a complex system with large lag, multiple-inputs and multiple-outputs (MIMO), nonlinear and difficult to model mathematically, and therefore even the implementation of classical control methods has been found difficult (Wang et al. 2012). The greenhouse climate control is challenging due to highly nonlinear interactions between the biological and physical subsystems and also to the strong coupling of the two main control variables: Temperature and humidity (Gurban and Andreescu 2012). However, PID controllers have mainly been applied to control air temperature, (Zhou et al. 2013) humidity, irrigation, and nutrients supply (Jaimes-Ponce et al. 2013). In several research works, PI/PID controllers are used as references (Cheng et al. 2013) because they are well known and also because researchers are looking for improvement in PID controllers performance by combining them with modern control approaches such as neural networks (Qu et al. 2011; Zuo et al. 2012) and genetic algorithms (Bounaama and Draoui 2011).